Abstract
The YOLO algorithm, an artificial neural network for target detection, was introduced with impressive performance metrics that outperformed existing algorithms, both in terms of speed and accuracy, and it outperformed the mainstream algorithms. It has also received widespread attention and research as a result, and has now evolved into its fifth generation. This paper compares the
localisation
and map building capabilities of different vision robots and examines the feasibility and s
基于YOLOv5的视觉定位机器人-20784字.docx